Abstract
Cricket, a game with a rich history, has evolved with various formats and competitions. The objective of this paper is to provide comprehensive insights into player strengths and weaknesses to assist teams by analyzing the player’s performance using multiple linear regression on the dataset, which includes batting, bowling, and fielding. As an optimizing strategy for the players, a Player Impact metric is developed using Genetic Algorithm to create a holistic and effective player performance metric. The data includes batting, bowling, and fielding statistics that assist in making strategic decisions. The metric was found to provide accurate assessments of player contributions to their teams, thereby aiding cricket analysis.
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Nayak, A.D., Aditya, A.S., Veliyath, A.J., Abraham, A.B., Bharathi, R., Sandesh, B.J. (2024). Player Performance Analysis. In: Senjyu, T., So–In, C., Joshi, A. (eds) Smart Trends in Computing and Communications. SmartCom 2024 2024. Lecture Notes in Networks and Systems, vol 948. Springer, Singapore. https://doi.org/10.1007/978-981-97-1329-5_27
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DOI: https://doi.org/10.1007/978-981-97-1329-5_27
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